• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2292-2298
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• 2009

In this paper, the lossy image compression algorithm using the quad tree and the bandlets is proposed. The proposed algorithm transforms input images by the discrete wavelet transform (DWT) and represents the geometrical structures of high frequency bands using the bandlets with a 8 block- size. In addition, the proposed algorithm searches the position information of the significant coefficients by using the quad tree algorithm and computes the magnitude and the sign information of the significant coefficients by using the Embedded Image Coding using Zerotrees of Wavelet Coefficients (EZW) algorithm. The compression result by using the quad tree algorithm improves the PSNR performance of high frequency images up to 1 dB, compared to that of JPEG-2000 algorithm and that of S+P algorithm. The PSNR performance by using DWT and bandlets improves up to 7.5dB, compared to that by using only DWT.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.73-80
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• 2019

In this paper, we propose an effective dynamic range compression (DRC) method of infrared images. A histogram of infrared images has narrow dynamic range compared to visible images. Hence, it is important to apply the effective DRC algorithm for high performance of an infrared image analysis. The proposed algorithm for high dynamic range divides an infrared image into the overlapped blocks and calculates Shannon's entropy of overlapped blocks. After that, we classify each block according to the value of entropy and apply adaptive histogram modification method each overlapped block. We make an intensity mapping function through result of the adaptive histogram modification method which is using standard-deviation and maximum value of histogram of classified blocks. Lastly, in order to reduce block artifact, we apply hanning window to the overlapped blocks. In experimental result, the proposed method showed better performance of dynamic range compression compared to previous algorithms.

• Journal of Korea Multimedia Society
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• v.25 no.1
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• pp.29-38
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• 2022

Although image compression is one of the essential technologies to transmit image data on a variety of surveillance and mobile healthcare applications, it causes unnecessary compression artifacts such as blocking and ringing artifacts by the lossy compression in the limited network bandwidth. Recently, image restoration methods using convolutional neural network (CNN) show the significant improvement of image quality from the compressed images. In this paper, we propose Image Denoising Convolutional Neural Networks (IDCNN) to reduce the compression artifacts for the purpose of improving the performance of object classification. In order to evaluate the classification accuracy, we used the ImageNet test dataset consisting of 50,000 natural images and measured the classification performance in terms of Top-1 and Top-5 accuracy. Experimental results show that the proposed IDCNN can improve Top-1 and Top-5 accuracy as high as 2.46% and 2.42%, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.902-908
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• 2013

This paper suggests to compress data selectively for improvement of data compression efficiency, not to perform unconditional compression on data. Whether to compress or not is determined by selective data distinction. By doing so, we can avoid unnecessary compression in the case of low compression efficiency. Cutting down the unnecessary compression, we can improve the performance of the pre-compression algorithm. Especially, the data algorithm which was already compressed could not be compressed efficiently in many cases, even if apply compression algorithm again. Even in these cases, we don't have to compress data unnecessarily. We implemented the proposed function actually and performed experiments with implementation. The experimental results showed normal operation.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.1
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• pp.17-24
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• 2012

There has been little study on the performance characteristics of the effective heat pump systems in the cooling mode using the two-stage compression cycles have hardly performed. In this study, the performance of the two-stage compression $CO_2$ cycle with an FI (flash intercooler) and the FGB (flash gas bypass) was investigated by using a theoretical method. The performance analysis was carried out with aby varyingiation (the indoor temperature, outdoor temperature, and 1st- and 2nd-stage EEV openings. As of a result, the coefficients of performance (COPs) of the Bbasic, FI, and FGB cycles were decreased by 28.5%, 22.1%, and 24.5%, respectively, for various outdoor temperature conditions. In addition to, the performance variation of the two-stage compression cycle was smaller than that of the single-stage compression cycle. The performance of the FI and FGB cycles was improved by 13.5%, and 6.9%, respectively, when the 1st-stage EEV opening was increased from 32% to 48%, and by 0.9%, and 2.6%, respectively, when the 1st- andthe 2nd-stage EEV opening was increased from 32% to 48%, andwas increased from 42% to 58%, respectively. The FI cycle showed anthe most improved performance for any given operating conditions.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.3
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• pp.45-58
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• 2020

In the current trend of increasing network traffic due to the popularization of cloud service and mobile devices, WAN bandwidth is very low compared to LAN bandwidth. In a WAN environment, a WAN optimizer is needed to overcome performance problems caused by transmission protocol, packet loss, and network bandwidth limitations. In this paper, we analyze the data deduplication algorithm of WANProxy, an open source WAN optimizer, and evaluate its performance in terms of network latency and WAN bandwidth. Also, we evaluate the performance of the two-stage compression method of WANProxy and Zstandard. We propose a new method to improve the performance of WANProxy by revising its data deduplication algorithm and evaluate its performance improvement. We perform experiments using 12 data files of Silesia with a data segment size of 2048 bytes. Experimental results show that the average compression rate by WANProxy is 150.6, and the average network latency reduction rates by WANProxy are 95.2% for a 10 Mbps WAN environment and 60.7% for a 100 Mbps WAN environment, respectively. Compared with WANProxy, the two-stage compression of WANProxy and Zstandard increases the average compression rate by 33%. However, it increases the average network latency by 2.1% for a 10 Mbps WAN environment and 5.27% for a 100 Mbps WAN environment, respectively. Compared with WANProxy, our proposed method increases the average compression rate by 34.8% and reduces the average network latency by 13.8% for a 10 Mbps WAN and 12.9% for a 100 Mbps WAN, respectively. Performance analysis results of WANProxy show that its performance improvement in terms of network latency and WAN bandwidth is excellent in a 10Mbps or less WAN environment while superior in a 100 Mbps WAN environment.

• Journal of information and communication convergence engineering
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• v.5 no.4
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• pp.305-310
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• 2007

In this paper, an analysis has been done on the performance of SCTP header compression by using Robust Reader Compression (ROHC)[1] method. And it is assumed that the operating mode for ROHC is unidirectional mode (U-Mode) and the possible states are IR and SO states. The throughput of SCTP packets in wireless link and the impact of size of W-LSB encoding window on throughput are discussed.

• Journal of the Korean Society of Industry Convergence
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• v.5 no.4
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• pp.295-299
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• 2002

Specific fuel consumption or specific power output characteristics of an internal combustion engine are likely, in conventional applications, the most important operating criteria. In this work, the test method for the engine performance was introduced in a compression ignition(diesel) engine.

• Journal of Hydrogen and New Energy
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• v.4 no.1
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• pp.1-9
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• 1993

To find performance and knock limit for compression ratio in hydrogen fueled engine, the variable compression ratio hydrogen fueled engine which was able to vary compression ratio during firing was manufactured and estimated. The characteristics of the variable compression ratio hydrogen fueled engine were as follows : 1) compression ratio variation by moving of cylinder head, 2) OHC which can be realized low S/V ratio, short flame propagation distance and unvariable configuration of combustion chamber for compression ratio variation, 3) direct injection of hydrogen gas to restrict back fire.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.221-224
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• 1996

This paper presents the ECG data compression using wavelet transform(WT) and adaptive fractal interpolation(AFI). The WT has the subband coding scheme. The fractal compression method represents any range of ECG signal by fractal interpolation parameters. Specially, the AFI used the adaptive range sizes and got good performance for ECG data compression. In this algorithm, the AFI is applied into the low frequency part of WT. The MIT/BIH arrhythmia data was used for evaluation. The compression rate using WT and AFI algorithm is better than the compression rate using AFI. The WT and AFI algorithm yields compression ratio as high as 21.0 without any entroy coding.